99% of CEOs Expect AI-Driven Job Cuts, With Young Workers’ Entry-Level Roles Most Exposed

Companies are racing to deploy generative AI as a way to cut labor costs, but workers are also the consumers who sustain corporate revenue. A Wharton School model calls this an “AI layoff trap”: each company captures the full savings from automation while sharing the resulting loss of demand with rivals. That incentive can push otherwise rational firms into an automation arms race, producing more displacement than is collectively optimal and ultimately hurting both workers and shareholders.

The Wharton paper, “The AI Layoff Trap,” by Brett Hemenway Falk and Gerry Tsoukalas was posted on April 11, 2026, and revised on June 2. It finds that retraining, universal basic income and worker equity cannot fully correct the demand externality, while a Pigouvian automation tax can. Separately, the World Economic Forum said in January 2025 that 59 of every 100 workers would need reskilling or upskilling by 2030 and 11 may not receive it — equivalent to more than 120 million people at medium-term risk of redundancy. Experts say governments should consider taxes and transition subsidies.

ServiceNow CEO Bill McDermott believes AI agents are evolving from assistive tools into a digital workforce capable of independently handling customer service, administrative and analytical tasks. If companies replace entry-level positions with automation, college graduates could lose a crucial route to gaining experience and find it harder to distinguish themselves in an AI-driven workplace. The impact could therefore extend beyond layoffs to reshape talent development and recruitment.

McDermott warned in 2026 that unemployment among college graduates could rise above 30% in the coming years. Even without a recession, employment conditions for the class of 2026 could still hit a record low. The discussion cited fintech company Block as an example, saying businesses had begun cutting jobs through AI automation and that pressure on entry-level white-collar work was shifting from forecast job losses to actual layoffs.